目的：开发一种在线图形处理单元（GPU）加速的基于蒙特卡罗的自适应放射治疗（ART）工作流程，用于笔形束扫描（PBS）质子治疗，以解决接受PBS治疗的患者的间期解剖学变化。
方法：使用我们内部开发的基于GPU加速的蒙特卡洛治疗计划系统开发了一个四步工作流程，以实现PBS的在线基于蒙特卡洛的ART。第一步进行基于微态demon的可变形图像配准（DIR），以将初始规划CT（pCT）上的轮廓传播到验证CT（vCT），以形成新的结构集。第二步骤在手动批准(涉及可能的修改)之后,利用传播的轮廓在vCT上执行初始计划的前向剂量计算。第三步骤根据验证剂量是否满足临床要求来触发计划的重新优化。将对第二步中的验证计划和第三步中的重组计划进行稳健评估。第四步涉及重新优化计划的两阶段(分娩前和分娩后)患者特异性质量保证(PSQA)。分娩前PSQA是将计划剂量与使用独立的快速开源蒙特卡洛代码计算的剂量进行比较，MCsquare.分娩后PSQA是将计划剂量与使用日志文件（spotMU，现货位置,和现货能量)在交付过程中收集。Jaccard指数（JI），骰子相似系数(DSC)，和Hausdorff距离（HD）用于评估第一步中传播的轮廓的质量。商业计划评估软件，ClearCheck™,被集成到工作流程中，以进行有效的计划评估。在第四步中使用3DGamma分析以确保重新优化的计划剂量的准确性。选择具有三个不同疾病部位的三个患者来评估PBS的在线ART工作流程的可行性。
结果：对于所有三名患者，发现传播的轮廓具有良好的体积一致性[JI（最低-最高：0.833-0.983）和DSC（0.909-0.992）]，但对于处于危险中的器官具有次优的边界符合性[HD（2.37-20.76mm）]。ClearCheck™评估的验证剂量显示，由于部分间的解剖变化，目标覆盖范围显着下降。对vCT的重新优化导致计划质量的极大改善至临床可接受的水平。PSQA的3DGamma分析证实了分娩前计划剂量的准确性（平均Gamma指数=98.74％，阈值为2％/2毫米/10％），并且在基于日志文件的交付之后(平均Gamma指数=99.05%,阈值为2%/2mm/10%)。完整执行工作流的平均时间成本约为858秒，不包括手动干预的时间。
结论：通过生成重新优化的计划，显着提高了计划质量，证明了拟议的PBS在线ART工作流程是有效和有效的。
OBJECTIVE: To develop an online graphic processing unit (GPU)-accelerated Monte Carlo-based adaptive radiation therapy (ART) workflow for pencil beam scanning (PBS) proton therapy to address interfraction anatomical changes in patients treated with PBS.
METHODS: A four-step workflow was developed using our in-house developed GPU-accelerated Monte Carlo-based treatment planning system to implement online Monte Carlo-based ART for PBS. The first step conducts diffeomorphic demon-based deformable image registration (DIR) to propagate contours on the initial planning CT (pCT) to the verification CT (vCT) to form a new structure set. The second step performs forward dose calculation of the initial plan on the vCT with the propagated contours after manual approval (possible modifications involved). The third step triggers a reoptimization of the plan depending on whether the verification dose meets the clinical requirements or not. A robust evaluation will be done for both the verification plan in the second step and the reopotimized plan in the third step. The fourth step involves a two-stage (before and after delivery) patient-specific quality assurance (PSQA) of the reoptimized plan. The before-delivery PSQA is to compare the plan dose to the dose calculated using an independent fast open-source Monte Carlo code, MCsquare. The after-delivery PSQA is to compare the plan dose to the dose recalculated using the log file (spot MU, spot position, and spot energy) collected during the delivery. Jaccard index (JI), dice similarity coefficients (DSCs), and Hausdorff distance (HD) were used to assess the quality of the propagated contours in the first step. A commercial plan evaluation software, ClearCheck™, was integrated into the workflow to carry out efficient plan evaluation. 3D Gamma analysis was used during the fourth step to ensure the accuracy of the plan dose from reoptimization. Three patients with three different disease sites were chosen to evaluate the feasibility of the online ART workflow for PBS.
RESULTS: For all three patients, the propagated contours were found to have good volume conformance [JI (lowest-highest: 0.833-0.983) and DSC (0.909-0.992)] but suboptimal boundary coincidence [HD (2.37-20.76 mm)] for organs-at-risk. The verification dose evaluated by ClearCheck™ showed significant degradation of the target coverage due to the interfractional anatomical changes. Reoptimization on the vCT resulted in great improvement of the plan quality to a clinically acceptable level. 3D Gamma analyses of PSQA confirmed the accuracy of the plan dose before delivery (mean Gamma index = 98.74% with a threshold of 2%/2 mm/10%), and after delivery based on the log files (mean Gamma index = 99.05% with a threshold of 2%/2 mm/10%). The average time cost for the complete execution of the workflow was around 858 s, excluding the time for manual intervention.
CONCLUSIONS: The proposed online ART workflow for PBS was demonstrated to be efficient and effective by generating a reoptimized plan that significantly improved the plan quality.
